MPRAMunich Personal RePEc Archive

Determinants of International TourismDemand for the Philippines: AnAugmented Gravity Model Approach

Roperto Jr Deluna and Narae Jeon

University of Southeastern Philippines, School of Applied Economics

March 2014

Online at http://mpra.ub.uni-muenchen.de/55294/MPRA Paper No. 55294, posted 14. April 2014 15:51 UTC

DETERMINANTS OF INTERNATIONAL TOURISM DEMAND FOR THE PHILIPPINES:

AN AUGMENTED GRAVITY MODEL APPROACH

Roperto S. Deluna Jr and Narae K. Jeon

Abstract

This study was conducted to investigate the determinants of international

tourism demand for the Philippines. This study employed a double-log

augmented form of gravity model estimated using the robust random

effects model. Results revealed that tourist arrival in the Philippines are

generally increasing from 2001 to 2012. Empirical estimation was

conducted to determine factors affecting Philippine tourism demand.

These factors include income, market size, and distance. Relative prices

was also identified which includes cost of living and price of goods and

services in the Philippines and other related tourism destination like

Malaysia, Indonesia and Thailand. Supporting variables like direct flights,

conflict, commonality in language and common colonizer between the

Philippines and source of origin of the tourist was also examined.

Furthermore, it also includes impact of calamity in the tourist home

country and common membership to ASEAN.

Empirical results show that tourist inflow is positively and significantly

affected by income of the origin country and is reduced by population

and distance. Relative low prices of tourism in term of cost of living and

prices of goods and services in the Philippines have no effect in attracting

inbound tourist. Furthermore, international demand for Philippine tourism is

not affected by relative prices of tourism in Malaysia, Indonesia and

Thailand as the competing tourist destinations. Conflict and common

colonizer between Philippines and country of origin are not significant

determinants of international tourism demand. Among the variables,

direct flights turned out to be the most significant factor that can

contribute to the increase in tourism demand of the Philippines.

Keywords: Tourism, augmented gravity, panel data-random effects,

tourism demand

Introduction

The Philippines is a sovereign island country in Southeast Asia situated in

the western Pacific Ocean. It is composed of 7,107 islands with vast

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features of tropical rainforests, mountains, beaches, coral reefs, and

diverse range of flora and fauna. These generate tourism which becomes

the major economic contributor in the Philippine economy. Tourism is an

economic activity, which is the largest and dynamically developing

sector in the country. Tourism generate demands from many different

industries, gives market power to those who have been able to join

different goods and services in a package and thus offer inclusive tours (IT)

to potential consumers (Ledesma, et al.,1999). According to the DOT

(2011), tourism is one of the three largest industries in the Philippines. The

tourism industry is mainly a consumer of inputs and producer of final goods,

hence, its impact on the output is relatively higher. Also, its

interdependence with other industries proves that other sectors do benefit

from the tourism sector (Yu, 2012).

Based on the 2013 travel and tourism competitiveness index from world

economic forum, the Philippines is the most improved country in the Asia

Pacific region. The country ranked 17th regionally and 82ndoverall, up by

12 places since 2012. Among the country’s comparative strengths are its

natural resources (44th), its price competitiveness (24th), and a very strong

and improving prioritization of the Travel & Tourism industry (this indicator

ranks 15th), as government spending on the sector (as a percentage of

GDP) is now 1st in the world. This is also supported by and increasingly

effective tourism marketing and branding campaigns around the world

(Blanke, 2013).

The market is concentrated in the industrialized countries of Asia, and

America. The numbers of tourist arrivals from Asia has increased from 56%

in 2001 to 62.5% in 2011, an increase of 6.5% for the last 10 years. Asia

remains the largest tourism market of the country. This is followed by

countries in America (20.4%), Europe (10.7%), Oceania (6.2%), and Africa

(0.1%). According to Department of Tourism (DOT), the tourist arrivals have

increased from 3.1 million to 4.3 million. This has becomes a major industry

to generate foreign revenue, investments, and exchange earnings.

Tourism contributed on the average, 5.8% to GDP from 2000 to 2011. As

measured by the share of tourism direct gross value added (TDGVA) to

total gross domestic product (GDP).

In terms of employment, tourism contributed on the average, about 9.8

percent to total employment from 2001 to 2011. The percentage share of

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tourism employment to total employment of the country is continuously

increasing with around 10.25% share in 2011. Travel & Tourism (T&T) has

continued to be a critical sector for economic development and for

sustaining employment. A strong T&T sector contributes in many ways to

the development of an economy (Blanke,2013).

Tourism has become one of the fastest-growing industries in the world

economy (William, 1991), with nations, states and communities funding

boards of tourism, to promote their locations and attract further

investment. Relative to other forms of international trade, tourism has

proved to be consistent and significant in its growth (Tse, 2001).

As mode of transportation was developing, it decreases cost of travelling.

People can visit abroad and enjoy foreign country's landscape, ruins,

customs, and culture among others. Through the popularization of tourism,

the government recognized the importance of tourism in the economy

(Korea Dictionary Research Publishing, 2010). During the recent decades,

tourism has become an important sector in the Philippines as a growing

source of foreign earning. Tourism industry is very important to the

economy and is identified as one of the major sources of economic

growth. Tourism revenues have grown to become the third largest industry

after oil and automobile industries. For the low-income countries

international tourism has become a major foreign exchange earner,

according to the UNWORLD Tourism Organization (Dilanchiev, 2012).

During 1997 to 1998, Koreans, Taiwanese, and Japanese’ tourist arrivals

decreased rapidly. The Asian financial crisis of 1997-98 was one of the

most dramatic economic events of recent times. These countries affected,

which had enjoyed a period of stability and rising living standards, saw

their currencies plummet in value and their economic plunged into slumps

that threw many of their citizens back into poverty. The crisis also ushered

in a period of heightened volatility in global markets (Boorman, et al.,

2000).This has impact to several markets and industries in the Philippines

including tourism receipts.

For effective tourism management, it is essential for the destination

country to measure its successes at any time and to determine the points

(factors) where certain management interventions (marketing,

development, etc.) can help to achieve or maintain this success (Papp

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and Raffay, 2011). Specific determinants of Philippine tourism demand

should be measured and identified for effective tourism management

strategy. Therefore serious attention should be given in studying the

factors that affect international tourist arrivals in the country.

In this paper, an augmented gravity model for tourism is used to identify

factors that influence foreign tourist arrivals, especially emphasizing on the

economic size, distance, population, direct flight, etc. In particular, this

study highlights the effects of economic relations between the countries

and their exchange rate. Also the study will estimate the elasticities of

income, tourism price, and other tourism variables of tourism demand for

the Philippines. The results of this study may be valuable for helping

professionals and policy-makers in the decision making process, related to

enhancing tourism industry in the country.

Objective of the Study

The overall objective of the study is to examine beyond the border factors

affecting Philippines tourism industry. Specifically, the study aims to:

a. present the trends of Philippines tourist arrivals,

b. identify these determinants affecting Philippine tourism and

c. to estimate elasticity of tourism demand in the Philippines.

METHODOLOGY

Conceptual Framework

Figure 1 shows the framework and variables included in this study. These

include several factors affecting tourist arrivals in the Philippines. The

subscript i refer to the Philippines and j is the country of origin at time t.

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Figure 1. Determinants of International tourist arrivals to the Philippines

Variables of the Study

The variables presented in the conceptual framework are defined

below:

Dependent Variable

The international tourism demand is often measured either in terms

of the number of tourist arrivals, tourist expenditure, and number of

tourist nights in the destination country (Ouerfelli, 2008). Data

limitations constrain the representation of the dependent variable.

In the case of this study, the available data have not permitted the

construction of tourism receipts or number of tourist night’s variables

for each of the origin countries. An alternative way of measuring

the volume of tourism is to use the number of tourists’ arrivals to the

Philippines from 24 countries that have available data to represent

International tourism demand for Philippines.

Determinants of Tourism Inflows Gross Domestic Product j,t Population j,t Distance i,j,t Relative Price (TCPIi,jt) Relative Exchange Rate (RREER i,j t) Relative PriceMalaysia (TCPI m,j,t) Relative PriceIndonesia (TCPI in,j,t) Relative PriceThailand (TCPI th,j,t) Dummy Variables Direct Flights i,j,t Conflict i,j,t Calamities j,t Language j Common Colonizer/s ASEANj

Tourist Arrivals

to the

Philippines

6

Independent Variables

a. Income (𝑮𝑫𝑷𝒋𝒕)–proxied by Real Gross Domestic Product at time t in

current US$ of the country of origin.

b. Population (Popjt) country of origin at time t, as proxy for market size.

c. Bilateral Distance (Distijt) between Manila (destination) and capital

cities of tourist home country measured in kilometers.

d. Relative Price of Tourism (TCPIi,j,t), tourism prices were described as

costs of living in the Philippines by the tourists from the origin

countries. This price variable is proxied by consumer price indices to

represent for the cost of tourism in destination (Philippines) relative

to the cost of living in the origin country. Demand theory

hypothesizes that the demand for international tourism is an inverse

function of relative prices, i.e., the lower the cost of living in the

destination relative to the origin country, the greater the tourism

demand and vice versa. We therefore expect a negative sign for

this variable. Tourism prices, which include the cost of goods and

services purchased by tourists in the destination country, are

measured by relative prices (Witt & Martin, 1987; Dritsakis & Gialitaki,

2001). The relative price variable TCPI is given by the indicative ratio

of the consumer price indices (CPI) of the destination country to the

origin countries.

𝑷 𝒋 𝒕 ( 𝑷 𝒕 𝑷 𝒋 𝒕

)

where: 𝑷 𝒕is the consumer price index in the Philippines in year t

𝑷 𝒋 𝒕is the consumer price index in the country of origin j, in year t

e. Relative Real Effective Exchange Rate (RREER i,j,t) rate between the

Philippines and origin countries which measures the effective prices

of goods and services in the Philippines relative to origin countries.

The relative real exchange rate is given by:

𝒋 𝒕 ( 𝒕

𝒋 𝒕)

where: 𝒕is the real effective exchange rate in Philippines, in

year t.

𝒋 𝒕is the real effective exchange rate in origin country j

in year t.

f. Relative Prices of Tourism in Competing Destination Countries which

are Malaysia (TCPIm,j,t), Thailand (TCPIth,j,t) and Indonesia (TCPIin,j,t).

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These are identified based on the similarity of tourism services and

attractions to the tourism of the Philippines. Relative Prices of tourism

in competing destinations was computed using equation 1 which

used CPI of Malaysia, Thailand and Indonesia as numerator and CPI

of the tourist home country as denominator to represent cost of

living of the competitive destination country.

g. Dummy Variables were included to further explain factors of

international tourism inflows to the Philippines. The following are as

follows:

Direct Flights (𝑫𝑭 𝒋𝒕) from the Philippines to the source of origin

of the tourist and vice versa. This took the value of 1, when

there is and 0, otherwise.

Conflict ( 𝒐𝒏𝒇 𝒋𝒕) between the Philippines and the country of

origin of the tourist. These could be conflict on trade, laws,

labor, territorial and resources. This variable took the value

of 1, when there is an existing conflict in a given year, and 0,

otherwise.

Calamity/ies ( 𝒂𝒍𝒋𝒕) in the origin country of the tourist which

could be man-made or natural calamities. This study limited

counting that typhoon (cyclone, hurricane), earthquake and

war. This took the value of 1, when there is and 0, otherwise.

Language (𝒍𝒂𝒏𝒈𝒋) is very crucial in tourism. This variable took

the value of 1, when the tourist country of origin can speak

English up to as 3rd language, and 0, otherwise.

Common Colonizer ( ) was included in the study to capture

similarity in customs, history and traditions. When the tourist

home country in any circumstances was under, the Hispanic,

European, Japanese and Americans or any of the following in

their history took the value of 1 and 0, otherwise.

ASEAN membership as dummy variable to capture if this

regional coalition of the Philippines has impact on increasing

inflows of international tourist to the Philippines. It took a value

of 1, when the country of origin is a member of ASEAN and 0

otherwise.

Data and Sources

The data of the study are secondary data to taken from different sources.

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Number of international tourist arrival was taken from Philippines Statistical

Yearbook from National Statistical Coordination Board (NSCB), and from

the Department of Tourism (DOT). The list of countries to include in the

study is presented in Table 1. Data on Gross Domestic product as proxy to

income and population as proxy for market size, real effective exchange

rates and consumer price indexes was taken from the World Bank

(http://data.worldbank.org/indicator/).

Table 1. List of countries included as sample of study.

Korea Australia Malaysia Thailand Switzerland Norway

USA Singapore UK Indonesia Netherlands Italy

Japan Canada Germany France Sweden Spain

China Hong

Kong

India Saudi

Arabia

Vietnam New

Zealand

Data on bilateral distance measured in kilometers, language and

common colonizer was secured from the Centre d'Etudes

Prospectivesetd' Informations Internationales (CEPII) which was developed

by Mayer and Zignago(2005).

Statistical Framework

The vast majority of the empirical papers on international tourism in the

literature are divided into two main types. The first consists of papers that

use modern time series and co-integration techniques in an attempt to

model and forecast the dependent variable, between one or several

pairs of countries. The second type includes papers that estimate the

determinants of international tourism flows using classical multivariate

regression framework (Halıcıoğlu, 2004; Eita and Jordaan, 2007). The

gravity model approach used in this paper can be counted in the second

class.

Gravity Model Approach on Tourism Demand

The gravity model belongs to the class of empirical models concerned

with the determinants of interactions. In its most general formulation, it

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explains a flow (of goods, capital, people etc.) from an area to another

area as a function of characteristics of the origin, characteristics of the

destination and some separation measurement. It was originally proposed

by Newton’s gravitational law. Tinbergen (1962) first used the gravity

model in analyzing flows of international trade. The basic assumption of

gravity model states that there is positive relation between bilateral trade

and GDP, while bilateral trade and distance are inversely related. The

basic formulation model is express as follow:

𝒓𝒂𝒅𝒆 𝒋 𝑨 (𝑮𝑫𝑷 .𝑮𝑫𝑷𝒋)

𝑫 𝒔𝒕𝒂𝒏𝒄𝒆 𝒋 (3)

For the econometric purposes, the equation (3) can be changed into a

linear form equation (4) by employing logarithm:

𝑇 (𝐺 . 𝐺 ) ( )

In estimating tourism demand, Rodrigue (2004) has used the Timbergen

Gravity Model and suit the tourism variables; some adjustment has been

made with the model. The model proposed by Rodrigue (2004) is:

𝑇 ( . )

where: 𝑇 stands for tourist arrival from country j to destination country i,

K is a constant term,

is a factor to generate movement of international tourism,

is a factors to attract movement of international tourism, and

is the distance between origin country j and destination country i.

This tourism demand gravity model in equation 5 can be transform into

linear equation the same way equation 3 was transformed in equation 4.

This basic model of gravity can be expanded to accommodate other

variables that generate and attract movement of international tourism

which is called an augmented gravity model.

Empirical Application

Recently, in the international tourism empirical literature, Gravity model

10

has been widely used to investigate the role of tourism. To achieve this

objective, demand factors of international tourism followed an

augmented form of Gravity Model. The study used 24 sample countries

from 2001 to 2012.The augmented gravity model tourism demand

function is presented in equation 6.

𝑇 𝑡 𝑓 𝐺 𝑡 𝑝 𝑡 𝑡 𝑇𝐶 𝐼 𝑡 𝑅𝑅𝐸𝐸𝑅 𝑡 𝑇𝐶 𝐼𝑚 𝑡 𝑇𝐶 𝐼 𝑛 𝑡 𝑇𝐶 𝐼𝑡ℎ 𝑡

𝐹 𝑡 𝐶 𝑓 𝑡 𝐶 𝑙 𝑡 𝑙 𝐶𝐶 𝑆𝐸 𝑁 6

Transforming equation 6 into a double log form eased the estimation and

interpretation of the estimated coefficients. The estimated coefficients of

the model are interpreted directly as tourism demand elasticities. The

double-log for the augmented gravity model of tourism demand is

presented in equation 7.

𝑙 𝑇 𝑡 0 𝑙 𝐺 𝑡 𝑙 𝑝 𝑡 3𝑙 𝑡 4𝑙 𝑇𝐶 𝐼 𝑡

5𝑙 𝑅𝑅𝐸𝐸𝑅 𝑡 6𝑙 𝑇𝐶 𝐼𝑚 𝑡 7𝑙 𝑇𝐶 𝐼 𝑛 𝑡 8𝑙 𝑇𝐶 𝐼𝑡ℎ 𝑡

𝐹 𝑡 𝐶 𝑓 𝑡 3𝐶 𝑙 𝑡 4𝑙 5𝐶𝐶 6 𝑆𝐸 𝑁

𝑡 7

Estimation Process

Standard gravity models generally use cross-section data for a particular

time period, such as one year, or over averaged data. However, panel

data models might provide additional insights, capturing the relevant

relationships over time and avoiding the risk of choosing an

unrepresentative year. Moreover, panels allow monitoring unobservable

individual effects between trading partners. Therefore, in order to

investigate the impact of gravitational factors on the tourist inflows, the

study employed the panel gravity model framework.

Panel data models have three basic approaches: They are pooled and

estimated by Ordinary Least Squares (OLS) or known as POLS. The second

approach is they are assumed to be motivated by fixed effects model

(FEM) and the third approach is the random effects model (REM). Each

approach has its own advantages and disadvantages. As Antonucci and

Manzocchi (2005) pointed out REM would be more appropriate when

11

estimating flows between a randomly drawn samples of trading partners

from larger population. On the other hand, FEM would be a better choice

than the REM when one is interested in estimating flows between a

predetermined selection of countries (Egger, 2000, 2005). Since the

sample of this study only contains tourist inflows of the Philippines from

different parts of the world based on availability of data, the REM might

be most appropriate specification.

To formally check the correct specification (REM or FEM) the study carried

out a Hausman test. The null hypothesis is that the preferred model is

random effects vs. the alternative the fixed effects. It basically tests

whether the unique errors (ui) are correlated with the regressors, the null

hypothesis is they are not (Green, 2008). To further test for random effects,

Breusch-Pagan Lagrange multiplier (LM) was employed. The LM test

identified appropriate model between a random effects regression (REM)

and a simple POLS regression. The null hypothesis in the LM test is that

variances across entities are zero. This is, no significant difference across

units (i.e. no panel effect). If the test failed to reject the null hypothesis,

them random effect is the most appropriate. Data preparation of study

used Microsoft Excel 2007, while estimation of the model used the

econometric package Stata Version 10.

RESULTS AND DISCUSSIONS

Trend of total tourist arrivals to the Philippines is increasing from 2001 to

2012 with a mild dip in 2003 and 2009 as impact of international crisis. The

decreasing tourist arrivals in the international economy have been

magnified by uncertainties in the US economy. Beyond 2009 it is observed

that arrivals increased rapidly than before.

The major markets of Philippine tourism are shown in table 2. It shows that

29% of the total international tourist arrivals in the country are South

Koreans, followed by USA, Japan, China, Australia and Singapore with

16%, 12%, 7%, 6%, 4% and 3.5%, respectively. There are 6 Asian countries

among the top 10 countries of tourist arrivals accounted for 58.33% in 2012.

Figure 2 presents the relationship of international tourist arrivals and

distance between the Philippines and the home country of the tourist. The

distance is divided into 4 groups with 5 thousand kilometers interval. The

12

size of the bubbles represents the volume of tourist arrivals, the larger the

bubble the higher the number of arrivals to the country. It revealed that

majority (62%) of the tourist arrivals to the Philippines are concentrated

from countries within the 5 thousand kilometers linear distance from the

Philippines. This is consistent with the concept of the gravity model which

further implies more tourist flow as the distance between the origin and

destination is minimal. This is usually explained in literatures as the

difference in travel cost. Countries with short distance imply lower

transportation cost of traveling, thus enhancing inbound tourist, ceteris

paribus. Generally, market shares of group countries in 4 ranges of

distance diminish as distance increases. The next distance ranges from 5

to 10 thousand kilometers distance accounts for around 10% of market

share, while 28% was accounted to countries within the 10 to 15 thousand

kilometers. This increased in market share in this distance range was

attributed to the market share of USA which is around 16%. It is notable

that Philippines and USA has a very tight economic relationship and

security partnership beyond distance. The last distance range accounts

for a very small market share of 0.1%, these are countries in Latin America,

which relating have a large range from the Philippine.

Table 2. Market share of major international tourist arrivals to Philippines,

2012.

From 2012 TA Market Share

(%) From

2012

TA

Market Share

(%)

S. Korea 1,031,155 29.0% Thailand 40,987 1.10%

USA 652,626 15.9% Indonesia 36,627 1.0%

Japan 412,474 11.60% France 33,709 0.90%

China 250,883 7.0% Saudi Arabia 30,040 0.80%

Australia 191,150 5.40% Switzerland 23,557 0.66%

Singapore 148,215 4.20% Netherlands 22,195 0.62%

Canada 123,699 3.5% Sweden 21,807 0.61%

Hong

Kong 118,666 3.32% Vietnam 20,817 0.58%

Malaysia 114,513 3.21% Norway 19,572 0.55%

UK 113,282 3.18% Italy 16,740 0.47%

Germany 67,023 1.90% Spain 15,895 0.45%

India 46,395 1.30% New

Zealand 14,100 0.39%

Source: National Statistical Coordination Board (NSCB)

Figure 2. Distance and market share of international countries to Philippines in 2012.

Source: National Statistical Coordination Board (NSCB)

Australia

Germany

Bangladesh

Turkey

India

France

Netherlands

Singapore

Sweden

Viet Nam

Norway

Italy

Spain

New Zealand

USA

Denmark

U.A.E

Hong Kong

Malaysia

Austria

Belgium

Thailand

Indonesia

Ireland

Brunei

Darussalam

Switzerland

Israel

Finland

China

Iran

Kuwait

Papua N.G.

Taiwan

Poland

Qatar

South Africa

Sri lanka

Canada

U.K

Pakistan

Bahrain

Cambodia

Brazil

Mexico

Japan

Greece

Egypt

Nizeria

Portugal

Argentina

Jordan

Belgium

S. Korea

Peru

Venezuela

Saudi Arabia

Russia

-5

0

5

10

15

20

Dis

tance

in t

housa

nd k

ilom

ete

rs

Market share

9.8%

Market share

27.8%

Market share

0.1%

Market share

62%

13

To formally identify factors determining international tourism demand for

the Philippines, an empirical analysis was conducted. As earlier discussed,

this study employed augmented form of gravity model using panel data.

To identify the proper specification of the panel data gravity model,

several tests was conducted. The Hausman test was used to identify the

appropriate specification of the model between fixed or random effects

models. Result of the test failed to reject the null hypothesis, therefore,

random effects model is preferred than the fixed effects model. This study

also considered the Breusch-Pagan Lagrange multiplier (LM) to decide

between a random effects regression and a simple OLS regression. Result

of the test rejected the null hypothesis that variances across cross sections

is zero. Therefore, there is a panel effect which suggest that random

effects model is appropriate in the estimation compared to OLS. Finally, to

control for heteroskedasticy robust random effects model was utilized in

the estimation of coefficients of the determinants of international tourism

demand for the Philippines.

Results of the robust REM are presented in Table 3. Results revealed that

Philippine tourism demand is significantly and positively affected by

income of its tourism markets. That is, a percent increase in income across

time and between countries will increase tourism demand by 0.41%. This is

consistent with the result of Munόz and Amaral (2000) which indicated

that as the country’s income increases, more of its residents can afford to

visit other countries, and therefore tourist arrivals are a positive function of

income or directly related to income.

Population and distance turned out significantly reducing tourist inbound

to the Philippines. On the average between countries and time, an

increase in population will decrease tourism arrivals by 0.19%, while a

percentage increase in distance will decrease also decrease tourist

arrivals by 0.38%. These results are consistent with the results of Karagöz

(2008), Hanafiah and Harun (2010), and Kosnan, et al. (2012), among

others.

Relative prices of Philippine tourism and cost of living in the Philippines

measured in terms of exchange rate and consumer price index turns out

14

insignificant. This means that the relative low prices of goods and

services, cost of living and tourism packages in the Philippines has no

effect on attracting/pulling tourist inbound. Furthermore, results revealed

that relative prices related to tourism in Malaysia, Indonesia and Thailand

has no effect on the international tourism demand of the Philippines.

Table 3. The robust random effect estimated coefficients of international

tourism demand of the Philippines, 2000-2012.

*significant at 5% nsnot significant

The existence of direct flights from the origin country to the Philippines is

highly significant in increasing tourism inbound. That is, direct flights from

origin to destinations will increase tourism inbound by 1.58%. Language

also played an important role in Philippine tourism, commonality in English

language between the Philippines and the tourist increases tourist

Variable Estimated

Coefficient

Robust Std.

Error P>|𝑧|

GDP 0.4071* 0.0560 0.000

Population -0.1873* 0.0372 0.000

Distance -0.3783* 0.0962 0.000

TCPI 3.2447ns 2.0987 0.122

Exchange rate 0.0134ns 0.0207 0.517

TCPI of Malaysia -3.3000ns 4.2668 0.439

TCPI of Indonesia -0.4808ns 0.9756 0.622

TCPI of Thailand 1.6893ns 4.6950 0.719

Direct Flight 1.5797* 0.1255 0.000

Conflict -0.0516ns 0.1126 0.647

Calamity 0.2766* 0.1045 0.008

Language 0.7282* 0.1157 0.000

Common

Colonizer

-0.1111ns 0.0955 0.245

ASEAN -0.9638* 0.1427 0.000

Constant 2.4470ns 1.5208 0.108

R2 : Overall = 0.7485

Within = 0.7335

Between = 0.9907

15

inbound by 0.73%. Results also revealed that calamity either natural or

man-made in the country of origin increase tourism of the country. This

might be due to the fact that most of the tourist inflows to the country are

from developed economies which have the capacity to move in case of

calamity. Common membership to ASEAN between the host and country

of origin reduces tourist inflow. This might reflect commonality of tourism

features in the ASEAN countries. Most of the tourist inflow of the Philippines

is mainly within the 5 thousand kilometers linear distance, however, mostly

from East Asian countries like Japan and South Korea. Conflict between

the Philippines and the home country of the tourist and commonality of

culture and traditions represented by common colonizer are not

significant indicators of tourism inbound.

The goodness of fit shows that 75% of the variability of the overall tourist

arrival panel data can be explained/predicted by the regressors included

in the model. Moreover, 99% and 73% variability can be predicted by

the regressors of the model if fitted between and within the model

respectively. Result of the F statistic test shows that the coefficients on the

regressors of the model are all jointly zero, which means that the

augmented gravity model of this study is significant in determining factors

of international tourism demand for the Philippines.

Summary and Conclusion

Tourism is one of the fastest growing industries in the world (William, 1991)

and has proved to be consistent and significant in its growth (Fletcher,

1997).This industry became a growing source of foreign earnings and one

of the sources of growth in the Philippines. Therefore, this study was

conducted to understand external factors that affect tourism demand of

the country. This is important component for planning and employing

effective tourism management, interventions and strategies to enhance

Philippine tourism industry.

In this paper, an augmented panel gravity model for tourism was used to

identify factors that influence foreign tourist arrivals. These factors include

income, market size, and distance. Relative prices was also identified

which includes cost of living and price of goods and services in the

Philippines. Other related tourism destination was also identified which are

the relative prices of tourism in Malaysia, Indonesia and Thailand.

Supporting variables like direct flights, conflict, commonality in language

16

and colonizer between the Philippines and source of origin of the tourist

was also examined. Furthermore, it also includes impact of calamity in the

tourist home country and common membership to ASEAN. The study

estimated the elasticities of income, tourism price, and other tourism

variables of tourism demand for Philippines.

Results revealed that tourist arrival in the Philippines is generally increasing

from 2001 to 2012. Furthermore, this increase is attributed to increasing

arrivals from countries in East Asia, particularly South Korea, Japan and

China. USA, Australia, Canada and Singapore also recorded notable

share from the total arrivals. In terms of distance, 62% of the market share

was accounted to arrivals from countries within the 5 thousand kilometers

linear distance. However, common memberships to ASEAN which is within

the 5 thousand kilometers distance turns out significantly reducing tourist

inbound which might be explained by commonality/substitutability of

tourism features.

Empirical results show that tourist inflow is positively and significantly

affected by income of the origin country and reduces by population and

distance. Relative low prices of tourism in term of cost of living and prices

of goods and services in the Philippines have no effect in attracting

inbound tourist. Furthermore, international demand for Philippine tourism is

not affected by relative prices of tourism in Malaysia, Indonesia and

Thailand as the competing tourist destinations. Conflict and common

colonizer between Philippines and country of origin are not significant

determinants of international tourism demand. Among the variables,

direct flights turn out to be the most significant factors that increase

tourism demand of the Philippines.

Recommendations

Based from the results of the study, the following are the

recommended:

a. The Philippines should further promote Philippine tourism

abroad, within the “It’s more fun in the Philippines”, as the

finding of the study suggests that prices are not significant

indicators of tourism demand. Therefore, it is hypothesized

that it might be the unique features of Philippine tourism that

matters most on tourism demand.

17

b. This promotion should focus on countries with relatively high

income like countries in East Asia, UK, Canada, among others.

c. More direct flights should be established to countries that

posed potential demand for the Philippine tourism.

d. Furthermore, the Philippines should enhance diversity of

languages through trainings and inclusion of major

languages in the curriculum of tourism related courses.

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